Abstract
Though there are a number of benefits associated with cellular manufacturing systems, its implementation (identification of part families and corresponding machine groups) for real life problems is still a challenging task. To handle the complexity of optimizing multiple objectives and larger size of the problem, most of the researchers in the past two decades or so have focused on developing genetic algorithm (GA) based techniques. Recently this trend has shifted from standard GA to hybrid GA (HGA) based approaches in the quest for greater effectiveness as far as convergence on to the optimum solution is concerned. In order to prove the point, that HGAs possess better convergence abilities than standard GAs, a methodology, initially based on standard GA and later on hybridized with a local search heuristic (LSH), has been developed during this research. Computational experience shows that HGA maintains its accuracy level with increase in problem size, whereas standard GA looses its effectiveness as the problem size grows.
Highlights
Introduction and Literature ReviewThe current manufacturing systems are facing a number of challenges in the form of globalization, shrinking product life cycles, variable demand patterns, more customized products, and ever decreasing “time to market.” These challenges can be tackled through effective and reliable manufacturing systems that can reduce the manufacturing cost and meet the manufacturing requirements timely and effectively, helping the manufacturer to compete with his competitors
Both the algorithms were given a run for similar number of generations; that is, if hybrid GA (HGA) got the best solution for a problem in 5 generations genetic algorithm (GA) was given a run for 5 generations
GA HGA GA with max. generations run for maximum number of generations (150) so that it should have sufficient opportunity to reach the optimum
Summary
Introduction and Literature ReviewThe current manufacturing systems are facing a number of challenges in the form of globalization, shrinking product life cycles, variable demand patterns, more customized products, and ever decreasing “time to market.” These challenges can be tackled through effective and reliable manufacturing systems that can reduce the manufacturing cost and meet the manufacturing requirements timely and effectively, helping the manufacturer to compete with his competitors. The current manufacturing systems are facing a number of challenges in the form of globalization, shrinking product life cycles, variable demand patterns, more customized products, and ever decreasing “time to market.”. These challenges can be tackled through effective and reliable manufacturing systems that can reduce the manufacturing cost and meet the manufacturing requirements timely and effectively, helping the manufacturer to compete with his competitors. Implementation of cellular manufacturing systems (CMS) can help the modern day manufacturers to face these challenges efficiently all in terms of cost, quality, and availability. Singh [7] reported a number of benefits such as reduced setup time and throughput, increased worker satisfaction, and product quality
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